Learning objectives
In the first part of this course, a few traditional methodologies in numerical analysis of experimental data will be described, aimed at extracting physical parameters through optimization processes. This course will describe a few spectroscopic methods that are based on the use of time correlation of visible photons that allow to extract information on dynamical processes of molecules. Methods are either monitoring fluctuations around equilibrium or relaxation after a perturbation. For each experimental method, a specific laboratory practice is proposed that will also take advantage of the numerical analysis introduced in the first part of the course.
At the end of this course students will learn how to interpret the significance of experimental results emerging from the optical methods covered in the course and become capable of performing experiments using the methods covered with the laboratory practice.
Prerequisites
Electromagnetism, classical geometrical and wave optics, quantum mechanics, condensed matter physics
Course unit content
Analisi di segnali mediante fitting non lineari
Photon time correlation methods
Time Correlated Single Photon Counting
Dynamic Light Scattering
Fluorescence correlation spectroscopy
Laboratory practice
Full programme
Analisi di segnali mediante fitting non lineari
Photon time correlation methods
Time Correlated Single Photon Counting
Dynamic Light Scattering
Fluorescence correlation spectroscopy
Laboratory practice
Bibliography
Principles of Fluorescence Spectroscopy, Third Edition, Joseph R. Lakowicz, Springer
Data Reduction and Error Analysis for the Physical Sciences, 2002, Philip Bevington, D. Keith Robinson, McGraw-Hill
Original research papers and reviews published on scientific journals
Teaching methods
The course consists in a series of lectures covering the fundamentals of the spectroscopic methodologies. For those methods available at this Department, laboratory practice will be taken.
Assessment methods and criteria
Student reports on the practice and the methods introduced in the course
Other information
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2030 agenda goals for sustainable development
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